The minimum learning rate ratio determines the lowest learning rate that will be used during training as a fraction of the initial learning rate. This is particularly useful when using learning rate schedules like "Cosine" or "Linear" that decrease the learning rate over time.

For example, if the initial learning rate is 0.001 and the min_learning_rate_ratio is set to 0.1, the learning rate will never drop below 0.0001 (0.001 * 0.1) during training.

Setting this to a value greater than 0 can help prevent the learning rate from becoming too small, which might slow down training or cause the model to get stuck in local optima.

- A value of 0.0 allows the learning rate to potentially reach zero by the end of training.
- Typical values range from 0.01 to 0.1, depending on the specific task and model.

This parameter cannot be set when using the **Constant** learning rate schedule.
